This commentary is dedicated to the memory of Diamantino de Jesus from the Universidade Nacional de Timor Loro-Sae who was an active member of the community of practice (CoP) until his untimely death on 8 September 2021.
In this paper, we investigate stable patterns of electroencephalogram (EEG) over time for emotion recognition using a machine learning approach. Up to now, various findings of activated patterns associated with different emotions have been reported. However, their stability over time has not been fully investigated yet. In this paper, we focus on identifying EEG stability in emotion recognition. To validate the efficiency of the machine learning algorithms used in this study, we systematically evaluate the performance of various popular feature extraction, feature selection, feature smoothing and pattern classification methods with the DEAP dataset and a newly developed dataset for this study. The experimental results indicate that stable patterns exhibit consistency across sessions; the lateral temporal areas activate more for positive emotion than negative one in beta and gamma bands; the neural patterns of neutral emotion have higher alpha responses at parietal and occipital sites; and for negative emotion, the neural patterns have significant higher delta responses at parietal and occipital sites and higher gamma responses at prefrontal sites. The performance of our emotion recognition system shows that the neural patterns are relatively stable within and between sessions.
Optimizing the Collection of Zakat Funds Using DigitalTechnology in Indonesia 1. Introduction Level of poverty in Indonesia is quite high. This indicates that the state has not been able to improve the welfare of its people, even though the state has a full obligation to provide welfare, peace and security to its people. Based on BPS data (2020), the percentage of poor people in March 2020 was 9.78 percent, an increase of 0.56 percentage points against September 2019 and an increase of 0.37 percentage points compared to March 2019. Meanwhile, the number of poor people in March 2020 was 26, 42 million people, an increase of 1.63 million people in September 2019 and an increase of 1.28 million people in March 2019. Of the many poverty numbers in Indonesia, a solution is needed to overcome this poverty rate. One of the efforts to reduce the poverty rate distribution of zakat funds.Zakat is one of the pillars of Islam, has enormous potential in reducing poverty. The potential for zakat Indonesia based on the results of Baznas research for zakat continues to increase every year. With this potential, the people in Indonesia will be able to prosper. But the realization that there is a large zakat potential is very l
The Internet of Things (IoT) has dominated the digital world by enabling thousands of physical devices to communicate with each other and share useful data over the Internet. With use cases spanning every sphere of modern life, the IoT is all set to revolutionize the traveling sector by extending services associated with safety, security, surveillance, tracking, comfort, and a lot more. This paper presents the design and implementation of a prototype Easy-Weigh-Out, based on the principles of the IoT which enables a user to run Android-based mobile application and view the weight of luggage and track its location without any contact with it. The hardware of the system is built around Arduino UNO microcontroller which interfaces with a load cell (20 kg) via A/D converter and a NEO-6M Global Positioning System (GPS) module for tracking of the bag. The system uploads data to a Cloud server using ESP8266 Wi-Fi module. Our results show the real-time weight and tracking of the bag at a click of a button as well as long-term data logging.
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